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Initial commit: Kompact context optimization proxy + benchmark suite
Multi-layer transparent HTTP proxy for LLM context optimization. Reduces token usage 40-70% with zero information loss. Transforms: TOON, JSON Crusher, Code/Log Compressor, Content Compressor (TF-IDF extractive), Schema Optimizer (TF-IDF tool selection), Observation Masker, Cache Aligner. Adaptive pipeline scaling. Benchmark suite using context-bench with NIAH, answer recall, effective ratio, and cost-of-pass metrics. Baselines: Headroom, LLMLingua-2, truncation, JSON minification. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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‎.github/workflows/ci.yml‎

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name: CI
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on:
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push:
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branches: [main]
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pull_request:
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branches: [main]
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jobs:
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test:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ["3.10", "3.12"]
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steps:
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- uses: actions/checkout@v4
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- name: Install uv
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uses: astral-sh/setup-uv@v4
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- name: Set up Python ${{ matrix.python-version }}
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run: uv python install ${{ matrix.python-version }}
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- name: Install dependencies
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run: uv sync --extra dev
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- name: Lint
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run: uv run ruff check src/ tests/
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- name: Test
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run: uv run pytest -v

‎.github/workflows/publish.yml‎

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name: Publish to PyPI
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on:
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release:
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types: [published]
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permissions:
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id-token: write
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jobs:
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publish:
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runs-on: ubuntu-latest
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environment: pypi
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steps:
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- uses: actions/checkout@v4
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- name: Install uv
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uses: astral-sh/setup-uv@v4
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- name: Set up Python
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run: uv python install 3.12
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- name: Build package
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run: uv build
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- name: Publish to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1

‎.gitignore‎

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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.egg-info/
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*.egg
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dist/
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build/
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.eggs/
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# Virtual environments
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.venv/
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venv/
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ENV/
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# IDE
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.idea/
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.vscode/
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*.swp
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*.swo
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*~
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.DS_Store
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# Testing
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.pytest_cache/
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.coverage
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htmlcov/
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.mypy_cache/
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.ruff_cache/
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# Benchmark reports (generated)
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benchmarks/reports/
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# HuggingFace cache (downloaded datasets)
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.cache/
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hub/
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# Environment
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.env
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.env.local
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# uv
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uv.lock

‎AGENTS.md‎

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# AGENTS.md — Kompact Context Optimization Proxy
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## What is Kompact?
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A transparent proxy that optimizes LLM context through multi-layer transforms.
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Sits between agents (Claude Code, Cursor, etc.) and providers (Anthropic, OpenAI).
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## Architecture
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```
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Request → Proxy → [Layer 1: Schema] → [Layer 2: Content] → [Layer 3: History] → [Layer 4: Cache] → Provider
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```
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## Entry Points
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| What | Where | Notes |
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|------|-------|-------|
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| CLI | `src/kompact/__main__.py` | `kompact proxy --port 7878` |
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| Proxy server | `src/kompact/proxy/server.py` | FastAPI, intercepts API requests |
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| Transform pipeline | `src/kompact/transforms/pipeline.py` | Orchestrates all transforms |
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| Configuration | `src/kompact/config.py` | Pydantic settings |
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| Core types | `src/kompact/types.py` | Message, ToolOutput, TransformResult |
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## Transforms (each is independent, pure function)
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| Transform | File | Layer | Typical Savings |
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|-----------|------|-------|-----------------|
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| TOON format | `src/kompact/transforms/toon.py` | 2 (Content) | 30-60% on JSON arrays |
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| Observation masker | `src/kompact/transforms/observation_masker.py` | 3 (History) | 50% on old tool outputs |
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| Cache aligner | `src/kompact/transforms/cache_aligner.py` | 4 (Cache) | Enables provider caching |
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| JSON crusher | `src/kompact/transforms/json_crusher.py` | 2 (Content) | 40-80% on structured data |
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| Schema optimizer | `src/kompact/transforms/schema_optimizer.py` | 1 (Schema) | 50-90% on tool defs |
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| Code compressor | `src/kompact/transforms/code_compressor.py` | 2 (Content) | ~70% on code blocks |
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| Log compressor | `src/kompact/transforms/log_compressor.py` | 2 (Content) | 60-90% on log output |
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## Key Invariants
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1. **All transforms are pure functions**: `list[Message] → TransformResult`
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2. **No transform modifies user messages** — only assistant/tool/system content
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3. **Every transform tracks `tokens_saved`** via `TransformResult`
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4. **Transforms are composable** — pipeline runs them in sequence
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## Documentation
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| Doc | Path | Purpose |
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|-----|------|---------|
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| PRD | `docs/prd.md` | Product requirements |
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| SDD | `docs/sdd.md` | System design |
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| Architecture | `docs/architecture.md` | Layer details |
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| Benchmarks | `docs/benchmarks.md` | Evaluation strategy |
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| Quality | `docs/quality.md` | Quality grades per domain |
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| Research | `docs/research/` | SOTA survey, competitors, economics |
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## Testing
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```bash
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uv run pytest # All tests
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uv run pytest tests/test_toon.py # Single transform
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uv run python benchmarks/compression_ratio.py # Benchmarks
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```
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## Quick Start
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```bash
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uv sync
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uv run kompact proxy --port 7878
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# Then: ANTHROPIC_BASE_URL=http://localhost:7878 claude
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```

‎LICENSE‎

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MIT License
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Copyright (c) 2025 Kompact Contributors
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎README.md‎

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# Kompact
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[![CI](https://github.com/npow/kompact/actions/workflows/ci.yml/badge.svg)](https://github.com/npow/kompact/actions/workflows/ci.yml)
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[![PyPI](https://img.shields.io/pypi/v/kompact.svg)](https://pypi.org/project/kompact/)
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[![Python 3.10+](https://img.shields.io/badge/python-3.10%2B-blue.svg)](https://www.python.org/downloads/)
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Context compression proxy for LLM agents. Reduces token usage 40-70% with zero code changes.
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## Quick Start
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```bash
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uv sync
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uv run kompact proxy --port 7878
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# Point your agent at it
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export ANTHROPIC_BASE_URL=http://localhost:7878
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```
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## Benchmarks
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### Offline Compression (12,795 examples)
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How much does each system compress, and does the answer survive? Evaluated with [context-bench](https://pypi.org/project/context-bench/).
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| Dataset | Examples | Kompact Compression | NIAH | Effective Ratio |
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|---------|----------|--------------------:|-----:|----------------:|
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| BFCL | 1,431 | 55.3% | 90% | 48.2% |
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| Glaive v2 | 3,959 | 56.6% | 100% | 56.6% |
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| HotpotQA | 7,405 | 17.9% | 91% | 8.8% |
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### End-to-End Quality (9,336 examples)
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Does compression change the LLM's answers? Each example sent through Claude (via [claude-relay](https://github.com/npow/claude-relay)) with no compression, Kompact, and [Headroom](https://github.com/headroom-ai/headroom) (SmartCrusher + ToolCrusher). **Contains** = answer found in LLM response.
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| Dataset | Examples | Baseline | Kompact | Headroom |
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|---------|----------|--------:|--------:|---------:|
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| **BFCL** | 1,431 | 29.3% | **36.4%** | 31.4% |
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| **HotpotQA** | 7,405 | 80.6% | 80.3% | 80.6% |
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Kompact **improves** answer quality on agentic workloads (+7.1% vs baseline, +5.0% vs Headroom on BFCL) — compression removes noise from tool schemas, helping the model focus. Quality is preserved on prose (HotpotQA within 0.3%).
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### Cost Impact
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Assuming 1,000 agentic requests/day with average 10K-token contexts (typical for tool-calling agents):
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| Model | Before | After (55% compression) | Monthly Savings |
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|-------|-------:|------------------------:|----------------:|
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| Claude Sonnet ($3/M) | $900/mo | $405/mo | **$495/mo** |
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| Claude Opus ($15/M) | $4,500/mo | $2,025/mo | **$2,475/mo** |
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| GPT-4o ($2.50/M) | $750/mo | $338/mo | **$412/mo** |
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```bash
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uv run python benchmarks/run_dataset_eval.py # offline compression
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uv run python benchmarks/run_e2e_eval.py # end-to-end through proxy
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```
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See [`benchmarks/README.md`](benchmarks/README.md) for full methodology and per-scenario results.
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## Development
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```bash
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uv sync --extra dev
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uv run pytest
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uv run ruff check src/ tests/
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```
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## License
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MIT

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